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Two-stage Optimal Scheduling of Community Integrated Energy system Considering Operation Sequences of Hydrogen Energy Storage systems

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Journal of Modern Power systems and Clean Energy 2025年第1期13卷 276-288页

作者： Wei Kong Kai Sun Jinghong Zhao School of Electrical Engineering Naval University of EngineeringWuhanChina Department of Electrical Engineering State Key Laboratory of Power System Operation and ControlTsinghua UniversityBeijingChina

The hydrogen energy storage system(HESS)integrated with renewable energy power generation exhibits low reliability and flexibility under source-load *** address the above issues,a two-stage optimal scheduling model considering the operation sequences of HESSs is proposed for commercial community integrated energy systems(CIESs)with power to hydrogen and heat(P2HH)*** aims to optimize the energy flow of HESS and improve the flexibility of hydrogen production and the reliability of energy supply for ***,the refined operation model of HESS is established,and its operation model is linearized according to the operation domain of HESS,which simplifies the difficulty in solving the optimization problem under the premise of maintaining high approximate ***,considering the flexible start-stop of alkaline electrolyzer(AEL)and the avoidance of multiple energy conversions,the operation sequences of HESS are ***,a two-stage optimal scheduling model combining day-ahead economic optimization and intra-day rolling optimization is established,and the model is simulated and verified using the source-load prediction data of typical days in each *** simulation results show that the two-stage optimal scheduling reduces the total load offset by about 14%while maintaining similar operating cost to the day-ahead economic optimal ***,by formulating the operation sequences of HESS,the operating cost of CIES is reduced by up to about 4.4%.

关键词： Community integrated energy system(CIES) hydrogen storage operation sequence two-stage optimal scheduling

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Mechanism Development of Separable Trimaran Robot With Multiple Rescue Methods

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Journal of Institute of control, Robotics and systems 2025年第1期31卷 29-36页

作者： Kim, Yugyeom Kim, Hyun-Sik Department of Mechanical System Engineering Tongmyong University Korea Republic of School of Electrical and Control Tongmyong University Korea Republic of

In recent years, the need for surface life-saving is gradually increasing as a response to accidents such as ship collisions in the marine environment. To solve this problem, there were approaches that launched life-saving rings, approached humans closely using rescue robots, and monitored life-saving status using drones. However, they did not solve the problem simultaneously in terms of rapidity, accuracy, and safety. To resolve this problem, a separable trimaran robot with a life-saving ring launcher and a drone is proposed and its mechanism is developed. Straightness, turning, launching, restoring and recover tests were performed to verify the validity of the proposed robot mechanism. Experimental results show that the proposed robot mechanism enables a rapid, accurate and safe surface life-saving. Therefore, it shows that the mechanism has meaningful components in surface life-saving and has the possibility of real system application. © ICROS 2025.

关键词： Drones

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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Camera-LiDAR Fusion for Detecting Traffic Law Violations in Surveillance systems

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Journal of Institute of control, Robotics and systems 2025年第3期31卷 187-195页

作者： Kim, Taek-Lim Jang, Byoung-Jin Yeon, Joo-Yeon Park, Tae Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of Department of Intelligent System and Robotics Chungbuk National University Korea Republic of

Traffic surveillance systems are essential for ensuring public safety and optimizing urban traffic flow by accurately detecting, classifying, and monitoring traffic law violations such as illegal parking and jaywalking. However, detecting such violations in dynamic urban environments poses significant challenges due to unpredictable conditions. Traditional camera-based systems excel in capturing visual details but suffer performance degradation under low light, occlusion, or complex intersection scenarios, leading to false positives and missed detections. Therefore, we propose a camera-LiDAR fusion-based traffic violation detection system. LiDAR's independence from lighting conditions complements camera capabilities, especially in night scenarios or occluded environments. Experimental results in a real-world urban environment demonstrate the system’s effectiveness in reducing false positives and missed detections compared to traditional camera-only approaches. This study underscores the potential of sensor fusion to improve traffic management systems and points out future research opportunities in challenging conditions. © ICROS 2025.

关键词： Urban transportation

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The Investigation of Data Voting Algorithm for Train Air-Braking system Based on Multi-Classification SVM and ANFIS

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Chinese Journal of Electronics 2024年第1期33卷 274-281页

作者： Juhan WANG Ying GAO Yuan CAO Tao TANG School of Electronics and Information Engineering Beijing Jiaotong University Graduate Department China Academy of Railway Science National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University

The pressure data of the train air braking system is of great significance to accurately evaluate its operation state. In order to overcome the influence of sensor fault on the pressure data of train air braking system, it is necessary to design a set of sensor fault-tolerant voting mechanism to ensure that in the case of a pressure sensor fault, the system can accurately identify and locate the position of the faulty sensor, and estimate the fault data according to other normal data. A fault-tolerant mechanism based on multi-classification support vector machine(SVM) and adaptive network-based fuzzy inference system(ANFIS) is introduced. Multi-classification SVM is used to identify and locate the system fault state, and ANFIS is used to estimate the real data of the fault sensor. After estimation, the system will compare the real data of the fault sensor with the ANFIS estimated data. If it is similar,the system will recognize that there is a false alarm and record it. Then the paper tests the whole mechanism based on the real data. The test shows that the system can identify the fault samples and reduce the occurrence of false alarms.

关键词： Multi-classification support vector machine Adaptive network-based fuzzy inference system Train air braking system Fault-tolerant voting Multi-sensors

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Comparative Analysis of Wearable and Computer Vision-Based Methods for Human Torso Posture Estimation 9

Comparative Analysis of Wearable and Computer Vision-Based M...

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9th International Conference on Mathematics and Computers in Sciences and Industry, MCSI 2024

作者： Muntean, Emanuel Leba, Monica University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9798350377224

This paper conducts a comparative analysis of human torso posture estimation methodologies, focusing on an inertial measurement unit (IMU) sensor coupled with an Arduino UNO as a wearable approach, and Kinect V2, utilizing OpenCV for posture analysis. The core objective of this study is to ascertain which method yields greater precision in the estimation of human torso posture. The IMU sensor, characterized by its wearability, provides the distinct advantage of unobtrusiveness and the capability to record motion across diverse environments. Conversely, Kinect V2 leverages computer vision techniques to derive posture estimations from visual data in real-time. Through comprehensive experimentation, this research evaluates the accuracy of both methodologies by juxtaposing their posture estimation outcomes. The findings of this investigation aim to significantly contribute to the enhancement of human posture estimation systems, with wide-ranging implications for health, sports, and ergonomics. © 2024 IEEE.

关键词： Ergonomics

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Feedback-Based Quantum control of Nuclei Spin in Ensembles 10

Feedback-Based Quantum Control of Nuclei Spin in Ensembles

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10th Indian control Conference, ICC 2024

作者： Kaushik, Vishesh Khaneja, Navin The System and Control Engineering department IIT Bombay Powai 400076 India

ISBN: (纸本)9798331517212

In this paper, we present a feedback-based framework for controlling the evolution of quantum spin states of nuclei within an ensemble. This approach allows for the selective excitation of nuclear spin states within specific pass bands of Larmor frequencies while leaving the nuclei outside the pass bands undisturbed. The control input sequence is designed in simulation and implemented using radio frequency pulses in the real system. © 2024 IEEE.

关键词： Feedback

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2D Posture Estimation of Human Arm 9

2D Posture Estimation of Human Arm

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9th International Conference on Mathematics and Computers in Sciences and Industry, MCSI 2024

作者： Rosca, Sebastian Daniel Leba, Monica Sibisanu, Remus University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9798350377224

Human pose estimation and automatic detection is a common task in Human-Computer Interaction but especially more capitalized in human-robot interaction inspired from biological form of human anatomy to realize a biomimetic control. In this sense, using human pose estimation it can be realized the whole human body posture estimation using anatomical human joints detection as inputs for specialized algorithms to calculate it based on key points obtained from a person Kinematic tree using regression, generation or part relation as models to estimate the optimal position from video or even from image. In this paper we propose a solution to estimate of 2D human arm posture of a subject using image capture as input for advanced machine learning algorithms to determine the subject joints position used to control in biomimetic manner a simulation of human like robotic arm with six degrees of freedom as a computer-aided model in Matlab-Simulink based on forward kinematics. © 2024 IEEE.

关键词： MATLAB

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controllability of heterogeneous networked sampled-data systems

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Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Evaluation of Feasibility for Optimal Motor Design Using Deep Q-Network 27

Evaluation of Feasibility for Optimal Motor Design Using Dee...

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27th International Conference on Electrical Machines and systems, ICEMS 2024

作者： Ran, Ji-Hoon Choi, Eui-Jin Park, Jong-Hoon Hong, Sun-Ki Hoseo University Department of System and Control Engineering Asan Korea Republic of Hoseo University Department of Information Control Engineering Asan Korea Republic of

ISBN: (纸本)9784886864406

The use of the reinforcement learning algorithm DQN(Deep Q-Network) can increase the design variables and offers the advantage of enabling more versatile motor optimization design. This paper evaluates the potential and advantages of reinforcement learning-based motor optimization design, which is still in its early stages globally. To demonstrate the performance of the proposed method, the geometry and drive conditions for reducing torque ripple of a FWSM(Field-Wound Synchronous Motor) using DQN were optimized. The proposed method exhibited excellent optimization performance, and it is expected that a more versatile optimization model can be developed by increasing the number of analysis cases. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Deep reinforcement learning

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